Search results

I tested the above suggestions, alongside ME/CFS, "tired", "always tired", and "fatigue" as well, for English, Scottish, and Irish ancestry. I sorted by Pearson, but also tested Spearman to see if large outliers are masking an association (which seems to be the case for Mississippi being an...

Relatively low correlations of Scottish or English ancestry with these four search terms: Note that the data for "type 1 narcolepsy" and "type 2 narcolepsy" might not be very reliable, because there looks to be very little search volume for these, and unlike most searches, states only have...

The correlation of English ancestry with early onset arthritis in Murph's Australia census analysis, and the many diseases highly correlated to ME/CFS in my USA Google Trends analysis made me wonder if places with British people have higher rates of many diseases, whether through genetic or...

An imaging flow cytometry method to study platelet-monocyte aggregates using Long COVID as a model Background Long COVID is characterised by persistent systemic inflammation and endothelial dysfunction, with increasing evidence implicating thromboinflammatory mechanisms. Platelet-monocyte...

I managed to do this, using gtrendsR, as suggested by Murph. I decided to have an AI code basically the whole script, and I am pleasantly surprised by how well it works. Essentially, the script is testing how well search interest in "chronic fatigue syndrome" correlates to search interest for...

Yeah, mine has always said "Disability". In a video about Trends, they seem to imply that any word under the term other than "Search term" means a Topic. Interesting that your R2 is higher. Just to clarify, the trends page you're using says "CFS/ME" and not "Myalgic encephalomyelitis/chronic...

That's funny. I had to look it up: - https://en.wikipedia.org/wiki/Irn-Bru

A hypothesis connecting dysgeusia due to defects in ATP-P2X3 signaling and fatigue in myalgic encephalomyelitis/chronic fatigue syndrome: lessons learned from long-COVID Srinivasan, Mythily; Joseph, Paule Valery Abstract Myalgic encephalomyelitis (ME)/chronic fatigue syndrome (CFS) is a...

I came back to this. I found out that the 210 "Metro" divisions for the US in Google Trends aren't just arbitrary shapes. They match up with Nielsen Designated Market Area (DMA) boundaries. (These DMAs are "a proprietary geography defined by Nielsen. They are non-overlapping geographic regions...

I've been using the Google Trends results for the ME/CFS Topic. Since Topics are more of a black box in terms of what search terms they contain, I wanted to check how the specific search term "ME/CFS" as well as other terms, correlate to ancestry. This whole thing started with English ancestry...

Just to check how well a Google Trends search for the ME/CFS "Topic" (which should be a combination of related terms, including other languages) compares to the data just for the specific term "ME/CFS", here is the data for both: R^2 = 0.52. That's basically only as good as British ancestry...

I just did some testing and the function works (most of the time - sometimes it seems to just hang.) I was getting worried about the R function getting different data than what I saw in the browser even though I was looking at both at the same time. Then I realized that my browser wasn't going...

Nice, I'll take a look. Python has (had) pytrends, another unofficial API, but it stopped working/being maintained a couple years ago, based on GitHub issues. This note from the maintainer of pytrends is a bit worrying: If Google gives fake data if downloading with a bot, it might affect the...

I think what could be interesting is looking for the best correlations of ME/CFS searches with other searches. For example, if the states that search most for ME/CFS also search most for "mono". There's no publicly available API for Google Trends, though, so data would have to be downloaded one...

Interesting idea. I just did a few quick plots using the time version of the Trends data, one each for worldwide, United Kingdom, and USA. I downloaded the whole timespan at once for each region, which gives one value per month. If downloading one year at a time, it gives one value per week, if...

A few more alcohol related stats. First, I looked at car crash deaths in which the driver had a blood alcohol content (BAC) greater than 0.01 or 0.08, as a proportion of all car crash deaths, from NHTSA. I picked the year 2015, since that seems like it would be the best year to compare to the...

Abstract 6275: Multidimensional analyses of pedigree, epidemiologic, and molecular data provide etiologic clues for myalgic encephalomyelitis/chronic fatigue syndrome. Moslehi, Roxana; Kumar, Anil; Dzutsev, Amiran [Line breaks added] Background Myalgic encephalomyelitis (ME)/chronic fatigue...

I was wondering about the genetics too. One way I was thinking of going about it was, if we assume the DecodeME regions cause ME/CFS, and if we assume being British increases risk of having ME/CFS, then we might expect that one or more of the DecodeME variants might be found more often in...

That's surprising, since the correlation seemed large for both prescription of alcohol addiction drugs as well as deaths due to alcohol from a totally different source. Not only that, but I also ran correlations against around 2800 more variables from a third source, the Correlates of State...

Thread for the study: A Comprehensive Examination of Severely Ill ME/CFS Patients, 2021, Chang et al